小波在数字图像边缘提取中的应用.doc
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小波变换在数字图像边缘提取中的应用
摘要:文中提出一种基于离散小波变换的针对数字图像边缘的有效检测算法。主要利用小波变换的多尺度分辨特性,对数字图像进行小波变换后的水平方向、垂直方向以及对角方向的细节信息进行提取,然后对图像中的边界点进行探测,达到提取出边界信息的目的。在处理过程中,首先对除噪以后的图像作一级2 - D 小波变换分解,得到一个低频和三个高频部分; 然后分别计算水平和垂直部分的绝对值均值,再分别计算水平和垂直方向的绝对值标准方差,根据绝对值标准方差构造四个新的二值矩阵,根据构造的矩阵修正水平和垂直方向细节信息,最后利用离散小波逆变换重构,得到检测后的图像。将重构后的图像进行边界提取。实验结果表明,算法效果良好。
关键词: 小波变换; 数字图像; 边缘探测; 纹理特征
Application of Wavelet Transform in Edge Detection for Digital Image
Abstract: An effective detection algorithm is proposed based on discrete wavelet transform for digital image edges. In this paper, the wavelet multiscale resolution is used for its characteristics of horizontal,v ertical and diagonal direction in order to extract the details, and then detect the boundary points of image,which will get the purpose for extracting boundary information. In the process,firstly, transforming the processed image without less noise into wavelet transform decomposition, the result is that a low frequency and three high frequency components are produced. The next work is calculating the mean of the absolute value of the horizontal and vertical portions respectively,and calculating the standard deviation of horizontal and vertical direction, according to the standard deviation,f our new binary matrix are constructed, the image matrix is corrected according to the horizontal and vertical detail information, the image will be obtained by the way of the inverse wavelet transform. And the boundary extraction is finished on the reconstructed image. The test results show that this method is effective.
Key words: wavelet transform; digital image; boundary detection; texture features
引言:18]中,主要考虑到细节信息的方向性,把水平方向和垂直方向的高频信息保留下来,并修改低频信息为细节部分的较大值,然后重构。虽然得到的结果边界信息更加突出,但原来的信息已部分改变。也有用小波变换模极大值法( Wavelet Transform Modulus Maxima,WTMM)
文中提出一种基于小波变换的图像边界提取的算法。该算法中仍然将重点放在小波高频信息的处理上。高频部分包含了图像的边缘信息,对于图像中的各个元素的边缘检测具有重要影响。首先,进行小波变换分析,尤其是二维小波变换的特点及其对图像处理的作用; 其次,对分解后的低频和高频部分系数根据一定的规则进行改变以更好地提取出边缘信息,这部分是文中的重点内容; 然后,用典型的图像实例对算法进行验证,说明其有效性
1. 2 - D
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